How has COVID-19 changed trip patterns by purpose in China?

IF 2.7 4区 工程技术 Q2 TRANSPORTATION SCIENCE & TECHNOLOGY
Enru Zhou, Jaeyoung Lee
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引用次数: 1

Abstract

COVID-19 has upended the whole world. Due to travel restrictions by governments and increased perceived risks of the disease, there have been significant changes in social activities and travel patterns. This paper investigates the effects of COVID-19 on changes to individuals' travel patterns, particularly for travel purposes. An online questionnaire survey was conducted in China, which incorporates questions about individuals’ sociodemographic and travel characteristics in three different periods of COVID-19 (i.e. before the outbreak, at the peak and after the peak; the peak here refers to the peak of the pandemic in China, between the end of January and 1 May, 2020). The results show that trip frequency decreased sharply from the outbreak until the peak, and drastically increased after the peak. Nevertheless, the data from this study suggests that it has not fully recovered to the level before the outbreak. Subsequently, a series of random parameters bivariate Probit models for changes in travel patterns were estimated with personal characteristics. The findings demonstrate that during the peak of the pandemic, residents who did not live in more developed cities reached low-frequency travel patterns more quickly. For travel purposes, residents of Wuhan, China resumed travelling for work, entertainment and buy necessities at a much higher rate than other cities. After the peak, students' travel for work, entertainment and to buy necessities recovered significantly faster than for other occupations. The findings would be helpful for establishing effective policies to control individual travel and minimize disease spread in a possible future pandemic.
新冠肺炎疫情如何改变中国的目的性旅行模式?
新冠肺炎已经颠覆了整个世界。由于政府的旅行限制和疾病风险的增加,社交活动和旅行模式发生了重大变化。本文研究了新冠肺炎对个人旅行模式变化的影响,特别是对旅行目的的影响。在中国进行了一项在线问卷调查,其中包括新冠肺炎三个不同时期(即疫情爆发前、高峰期和高峰期之后;这里的高峰期是指2020年1月底至5月1日期间中国疫情的高峰期)个人的社会人口统计和旅行特征问题。结果表明,从疫情爆发到高峰,出行频率急剧下降,高峰过后出行频率急剧上升。尽管如此,这项研究的数据表明,它还没有完全恢复到疫情爆发前的水平。随后,根据个人特征估计了一系列旅行模式变化的随机参数双变量Probit模型。研究结果表明,在疫情高峰期,不住在较发达城市的居民更快地达到低频旅行模式。出于旅行目的,中国武汉的居民恢复工作、娱乐和购买必需品的比率远高于其他城市。高峰过后,学生的工作、娱乐和购买必需品的旅行恢复速度明显快于其他职业。这些发现将有助于制定有效的政策,控制个人旅行,并在未来可能的大流行中最大限度地减少疾病传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transportation Safety and Environment
Transportation Safety and Environment TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
3.90
自引率
13.60%
发文量
32
审稿时长
10 weeks
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